September 27, 2019

How Companies Leverage AI to Drive Sales Revenue

By Mike Orr, COO, Grapevine6

Is artificial intelligence (AI) much smarter than either of us? Yes. But it isn’t a human kind of smart.

When you give an AI-powered platform a “learned task” along with a huge dataset, it will perform that task faster and more effectively than an entire team of people – but that doesn’t mean it can sell.

Succeeding with AI in digital selling is not about replacing anyone with AI – and it isn’t about designing an AI that can truly sell (at least, not in the near term).

What AI Means for Sales
AI today is about finding tasks, traditionally performed by salespeople, that can be replaced by a specific trained AI and carried out at scale. A great example of this is Tugboat Logic, a company that is applying AI to everyone’s favorite activity – completing RFPs! Apps that harness AI to augment salespeople are the most valuable.

AI Enables Risk Management
One of the areas where AI is most successful is risk management. Companies that provide compliance integration are perfect examples of how artificial intelligence facilitates the selling process. Lots of companies that sell in regulated environments suffer this dilemma. Digital selling requires this highly responsive sales force, which quickly produces an impressive volume of data.

In regulated markets, speed and freedom can pose huge legal risks. Even in unregulated markets, it only takes one post out of a thousand to compromise a brand. Natural language processing (NLP) removes a lot of that risk by scanning the communications that flow through social media at a speed fully manual supervision can never match. This enables bigger and bigger regulated companies to fully deploy digital selling initiatives. Compliance AI technology, supervised by an experienced compliance team, can augment that existing team and improve their ability to protect the company from risk without sacrificing authenticity.

Using AI in Sales
To discover how AI is transforming sales, consider where AI has been successful in other applications. According to Angel List, there are 2,200+ AI start-ups, and over 50 percent have emerged in just the past two years. It’s therefore wise for these firms to focus on addressing a specific business challenge.

NLP is one branch of AI with a ton of applications: Companies and academics have used it for everything from summarization to translation to sentence classification. NLP technology designed to summarize an article can become an AI application that feeds concise information to your sales force. The AI that provides highly accurate translations can help your sales force localize content.

AI in sales isn’t about reinventing the wheel if you want it to succeed. It’s about recognizing where a technology has potential, and then using it to improve the sales process incrementally.

Training for AI Is Required
A lot of the success and failure of AI will depend on the training provided to end users.

Some think AI is a magic bullet. While it’s a very smart, advanced computer program, at the end of the day it is still a computer program. Successful companies will find ways for employees to experience and experiment with AI. That’s the best way for employees to realize its potential and limitations.

AI is a game changer for many industries, but it doesn’t change the basic rules. Like any technology, it’s not only about AI itself, it’s about training employees to best use that technology.

For AI to be effective, companies must design in feedback loops – because AI feeds on data as it learns. Additionally, most decision models perform best when there’s human input informing the decision making. Compliance is a great example, but that’s a situation where you have an AI performing a task supervised by people. The smart AI approach is to find the gray-area content and have humans supervise the decisions. AI can then learn to narrow the gray area – freeing resources or enabling scale.

AI Privacy Risks
Most risks with AI involve privacy. Recently there has been a lot of talk about the misuse of personal data, which applies to AI and sales.

IBM estimated, in 2013, that half the data in the world had been produced in the previous two years, and that sheer quantity of data is only increasing. Besides the plethora of data, there’s a huge risk in how that data is used or misused.

Some AI products in social selling cross the line, and companies that use AI must be educated on the risks of violating privacy, with regulations such as GDPR.

Quality of data is as important as the quantity. Regarding the explosion of data, Carl Sagan correctly observed that not all bits are created equal. Much like marketing, there is a critical need in sales to create clean data and extract insights to advance the sales process. Successful salespeople have always been sleuths at collecting clues about their prospects’ unique business needs. This human skillset is invaluable, as those clues drive the most valuable intelligence in AI – ultimately driving sales revenue.

Mike Orr is co-founder of Grapevine6. Contact him at Morr@grapevine6.com or on LinkedIn.